STICERD Econometrics Seminar Series
Contamination Bias in Linear Regressions
Michal Kolesár (Princeton University), joint with Paul Goldsmith-Pinkham (Yale) and Peter Hull (Brown)
Thursday 09 March 2023 14:00 - 15:30
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Unless otherwise specified, in-person seminars are open to the public.
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About this event
We study regressions with multiple treatments and a set of controls that is flexible enough to purge omitted variable bias. We show these regressions generally fail to estimate convex averages of heterogeneous treatment effects; instead, estimates of each treatment’s effect are contaminated by non-convex averages of the effects of other treatments. We discuss three estimation approaches that avoid such contamination bias, including a new estimator of efficiently weighted average effects. We find minimal bias in a re-analysis of Project STAR, due to idiosyncratic effect heterogeneity. But sizeable contamination bias arises when effect heterogeneity becomes correlated with treatment propensity scores.
STICERD Econometrics seminars are held on Thursdays in term time at 14.00-15.30, in SAL 3.05, unless specified otherwise.
For further information please contact Sadia Ali: firstname.lastname@example.org.
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